Disruptive software solutions changing the industry : how’s AI transforming decision making process in healthcare

Abstract

With the rapid development of Artificial Intelligence (AI) technology, the prospect of AI application in the healthcare industry is becoming more and more extensive, especially the potential in medical decision support systems (DSS) is becoming more and more obvious. AI technology can help doctors to quickly diagnose diseases, assess risks and provide personalised treatment plans through the in-depth analysis of large amounts of medical data. However, the application of AI in medical decision-making still faces many challenges, including data quality, model interpretability, privacy protection, and other issues. The aim of this paper is to design and build an AI-based healthcare decision support system (AI-HCDS) to enhance the system's performance in disease diagnosis, risk prediction, and personalised treatment through the integration of multiple AI techniques (e.g., machine learning, deep learning, and natural language processing). In this study, I first collected and preprocessed medical data, used multiple AI models for training, and finally constructed an efficient and accurate medical decision support system. Through experimental analysis, the system shows high accuracy and stability in multi-task learning, and is able to provide powerful decision support for doctors and customise personalised treatment plans for patients. Finally, this paper discusses the advantages and challenges of AI in medical decision-making, and proposes future development directions and optimisation solutions.